SCHEDULING AND FORECASTING METHODS FOR PRODUCTION IN HOME INDUSTRY BUSINESSES

Abstract

The need for additional food (snacks) determines a person's choice of consumption. Cassava chips are a snack that contains a source of energy from complex carbohydrates, fiber for digestion, and antioxidants such as vitamin C and beta-carotene that protect the body. A home industry makes cassava chips using a simple method, namely only washing, slicing, frying, slicing, and wrapping without using production scheduling and forecasting methods. This results in inconsistent production quantities. This condition also creates excess and shortages in production results that impact on not meeting consumer desires. This study aims to provide input to home businesses by using sequencing methods, namely short processing time (SPT) for scheduling and moving averages for production forecasting, to obtain scheduling and forecasting results that will serve as references in the cassava chip manufacturing process. From the data owned by this home industry, both quantitative and qualitative data, results are obtained that can be used as references. The results of the two methods are the average work time is 60 minutes, Job utilization with the shortest processing time is 35.8%, the average job in the system is 2.79 jobs or rounded to 3 jobs, the average job delay is 48.5 minutes or rounded to 49 minutes. Meanwhile, the amount to be made (processed) is adjusted from the calculation of the available data forecast, so that from this we get the amount that can be used as a reference in its implementation.